65 citations · 218 across the 26 of their papers we have counts for
4 papers · 1 filter
MIA-Former: Efficient and Robust Vision Transformers via Multi-grained Input-Adaptation
Zhongzhi Yu, Yonggan Fu, Sicheng Li +2
ViTs are often too computationally expensive to be fitted onto real-world resource-constrained devices, due to (1) their quadratically increased complexity with the number of input…
Early-Bird GCNs: Graph-Network Co-Optimization Towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets
Haoran You, Zhihan Lu, Zijian Zhou +2
Graph Convolutional Networks (GCNs) have emerged as the state-of-the-art deep learning model for representation learning on graphs. However, it remains notoriously challenging to t…
CPT: Efficient Deep Neural Network Training via Cyclic Precision
Yonggan Fu, Han Guo, Meng Li +4
Low-precision deep neural network (DNN) training has gained tremendous attention as reducing precision is one of the most effective knobs for boosting DNNs' training time/energy ef…
SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training
Xiaohan Chen, Yang Zhao, Yue Wang +6
The record-breaking performance of deep neural networks (DNNs) comes with heavy parameterization, leading to external dynamic random-access memory (DRAM) for storage. The prohibiti…